Papers by Mohammad Albinhassan

    1 papers
    Learning and Enforcing Context-Sensitive Control for LLMs (2025.acl-srw)

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    Challenge: Large Language Models (LLMs) have been able to achieve syntactic correctness but ensuring semantic validity requires additional mechanisms.
    Approach: They propose a framework that automatically learns context-sensitive constraints from LLM interactions through syntactic exploration and constraint exploitation.
    Outcome: The proposed framework outperforms larger models and state-of-the-art models in learning and generation of large LLMs.

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